There is considerable interest in measuring the usage of media data accessed by an audience via a network or other source. In order to determine audience interest and what audiences are being presented with, a user's system may be monitored for discrete time periods while connected to a network, such as the Internet. Large amounts of data may be compiled in a relatively short period of time, requiring substantial processing, bandwidth and storage resources.
There is also considerable interest in providing market information to advertisers, media distributors and the like which reveals the demographic characteristics of such audiences, along with information concerning the size of the audience. Further, advertisers and media distributors would like the ability to produce custom reports tailored to reveal market information within specific parameters, such as type of media, user demographics, purchasing habits and so on.
In addition, there is substantial interest in the ability to monitor media audiences on a continuous, real-time basis. This becomes very important for measuring streaming media data accurately, because a snapshot or event generation fails to capture the ongoing and continuous nature of streaming media data usage.
Based upon the receipt and identification of media data, the rating or popularity of various web sites, channels and specific media data may be estimated. It would be advantageous to determine the popularity of various web sites, channels and specific media data according to the demographics of their audiences in a way which enables precise matching of data representing media data usage with user demographic data.
It is also important to ensure relatively little if no interference with the user and the user's system by this monitoring. If the monitoring system unduly interferes with the user or the user's system, individuals will be reluctant to allow monitoring of the media data presented to them. At the same time, it is necessary to minimize such interference to avoid influencing audience behavior which could bias the monitored data.
However, as mentioned above, vast amounts of media data may be presented to a user, through a user system, in a very short period of time. Where the user's system is employed to monitor media data usage, substantial user system resources are required by existing systems to accurately monitor even for specific media data presented over a short time period, which raises the possibility of interference with the operation of the user's system.
In addition, a unique problem is encountered when monitoring usage of streaming media data from a network. Multimedia streaming delivers a steady stream of video and/or audio over the network connection. For instance, the stream may include multiple independent multimedia segments such as advertising. Further, the stream may be associated with a particular network resource such as a web page that offers content tied to the streaming media data. There are also multiple protocols and delivery technologies that result in many different types of streaming encoding, servers and players. Also, the streaming media data is often associated with additional media data having diverse formats such as but not limited to HTML, e-mail, and instant messaging.
The options for accessing and presenting media data, as well as the means for delivering media data develop and evolve at ever greater rates. For many years, over-the-air radio and television broadcasting distributed listening and viewing data in fixed formats and in long-established and well-defined channels. The task of audience measurement in this environment was relatively much simpler than now, when media data is delivered in many more formats through numerous communication systems and protocols which continually evolve. Also, there are vastly more sources for media data at this time, along with a multitude of devices and user agents for accessing and presenting media data. To be useful in the long term, an audience measurement system must be flexible and scalable while remaining cost efficient.
Therefore, systems and methods are desired that will accurately record the media data a user is accessing or is presented through a user system, while at the same time not interfering with the user or noticeably burdening the user system.
It is also desired to match the user's demographic data with data representing what was accessed or presented, and to do so in a manner which is accurate, efficient and as precise as possible.
Systems and methods are further desired that will enable advertisers, media distributors and the like to produce customized media usage reports.
Systems and methods are also desired that will accurately monitor streaming media data on a continuous and essentially real-time, basis.
It is also desired that the systems and methods be flexible and scalable, yet cost effective, enabling commercially viable media data usage monitoring despite large, rapid and unpredictable changes in usage patterns and in the needs of those who make use of reports based on the data gathered.